looking for someone who can fix AI chat bot

@extreamcode

Hi there, Asad- I’ve read your brief and I’m confident I can pinpoint where the intent-handling flow breaks and restore context-aware replies in your Python 3.9, FastAPI, Rasa NLU/Dialogues stack. I’ll methodically audit the Dockerized setup, Redis-backed sessions, and the AWS ECS deployment, correlating CloudWatch traces and failing conversation logs to reproduce and fix the issue. With 15+ years in AI chatbots, API-driven architectures, and robust DevOps, I’ll deliver a clean patch/PR with a concise root-cause summary and a short technical note on what changed and why. What you’ll get: • Fixed source code or PR that restores correct, context-aware responses • Brief root-cause analysis and the changes made • Evidence: test conversations produce expected answers and a 30-minute free-flow chat runs without fallbacks • A quick plan for deployment and verification in your AWS/docker setup I’ve shared an initial estimate based on your description, and once we go over a few technical details, I’ll confirm the exact cost and delivery schedule. Let’s align on the repro steps and testing approach, then I’ll push the patch for review. Best regards, Asad

@AZTURK1

Hi there, I reviewed your stack: Python 3.9 FastAPI service calling Rasa NLU/dialogue, Redis session state, all containerised in Docker on AWS ECS; those logs and CloudWatch traces point to an intent-handling race and session deserialization gap I can fix. - Fixed source code or PR that restores context-aware intent routing and correct slot/state reads in the Rasa-FastAPI flow - Short technical summary showing root cause (race/serialization bug) and exact code changes plus unit/integration test updates - Proof package: replay of your failing conversation logs proving expected answers and a 30-minute free-flow run without fallback triggers - Risk/quality-control: staged deployment and rollback plan with backup checkpoint and post-deploy validation Skills: ✅ FastAPI ✅ Rasa NLU/dialogue ✅ Redis ✅ Docker on AWS ECS ✅ Context validation, session handling and post-deploy testing Certificates: ✅ Microsoft® Certified: MCSA | MCSE | MCT ✅ cPanel® & WHM Certified CWSA-2 I’m available to start immediately; Should I run fixes directly against your production ECS service or push changes to a staged/test task for validation first? Best regards,

@hr157

Hi, With 10+ years of full-stack and AI workflow experience, I’ve worked on debugging conversational systems, API orchestration, state-management issues, and production AI integrations running in containerized environments. My approach: - Reproduce failures locally using your logs/traces - Trace the full request lifecycle: FastAPI → Rasa NLU → policies/actions → Redis state → response pipeline - Identify root-cause patterns (not just isolated fixes) - Validate fixes against supplied conversations + extended free-flow testing What I’ll deliver: - Clean fix/PR with reviewed, maintainable code - Root-cause technical summary - Stable, context-aware response handling - Validation against your failing conversation cases - Reduced fallback/empty response scenarios - ECS/Docker-safe implementation Areas I’d specifically inspect: - Intent thresholds/fallback policy - Slot/session persistence in Redis - Async race conditions - Tracker state corruption - Custom action failures/timeouts - Docker/ECS environment inconsistencies - Webhook/response formatting issues Once access is shared, I can begin with log tracing and isolate the failure path quickly. Best regards

@joseteixeira06

Hi , Good afternoon! I am an expert mobile computer programmer with skills including Linux, AI Chatbot Development, Ubuntu, FastAPI, Python, Redis, Software Architecture and Docker. Please contact me to discuss more about this project. Have a great time

@adily1

Hey , I just finished reading the job description and I see you are looking for someone experienced in Python, Software Architecture, Redis, Ubuntu, AI Chatbot Development, Docker, Linux and FastAPI. This is something I can do. Please review my profile to confirm that I have great experience working with these tech stacks. While I have few questions: 1. These are all the requirements? If not, Please share more detailed requirements. 2. Do you currently have anything done for the job or it has to be done from scratch? 3. What is the timeline to get this done? Why Choose Me? 1. I have done more than 250 major projects. 2. I have not received a single bad feedback since the last 5-6 years. 3. You will find 5 star feedback on the last 100+ major projects which shows my clients are happy with my work. Timings: 9am - 9pm Eastern Time (I work as a full time freelancer) I will share with you my recent work in the private chat due to privacy concerns! Please start the chat to discuss it further. Regards, Adil.

@usamaansari786

Hi, With my 15+ years of experience and track record of delivering 150+ successful projects, I am confident in my ability to tackle and resolve your AI chatbot issues. I specialize in "Build Once, Automate Forever" workflows and have expertise with numerous AI technologies including Rasa NLU/dialogue which you use in your stack. This hands-on experience has equipped me to quickly dig through the codebase, identify root causes, implement clean patches, and realign your bot's intent handling flow to provide consistently accurate and context-aware answers. Furthermore, my extensive proficiency with Python (Python 3.9 being the heart of your stack), FastAPI, Docker, AWS ECS and Redis for session state management make me highly adept at navigating your development environment with ease. Alongside fixing the source code and providing a technical summary of my changes as requested, I can also confidently assure you that the supplying test conversations will yield expected answers and a 30-minute free-flow-chat sans fallback triggers. Lets have a chat warm regards USama Ansari

@goranm16

Hi, this sounds less like a “chatbot quality” issue and more like a broken intent/session path where Rasa confidence, Redis state, or fallback routing is losing context before FastAPI returns the reply. I’ve fixed similar bot issues where users were getting blank responses because the dialogue state was being overwritten between turns. The fix was to replay failing conversations, trace the intent/action path, then patch the state handling and add regression checks around the exact broken flows. I’d start by reproducing your failing logs locally in Docker, then compare Rasa events, Redis session values, and FastAPI responses against CloudWatch traces. The main risk is fixing one symptom while leaving another fallback path broken, so I’d validate with your supplied conversations plus a longer free-flow run before calling it done. Thanks!

@toqeer74

The frequent empty or incorrect replies from your AI chatbot indicate a critical flaw in the intent-handling flow that requires immediate investigation. Given the technical stack of Python 3.9, FastAPI, and Rasa NLU, I can dive into the codebase to analyze the dialogue management system, utilizing the provided conversation logs and CloudWatch traces for diagnostics. With 7 days for the initial deliverable, the outcome will consist of a patched pull request, a concise summary of the root cause, and validation through comprehensive test cases. What does success look like for you at the end of this project?

@aaronrobs

⭐⭐Hi There⭐⭐ I HAVE EXPERIENCE BUILDING AI chatbots using Python, FastAPI, and Rasa NLU, deployed with Docker on AWS ECS. I can help debug your intent-handling flow by analyzing your codebase, conversation logs, and CloudWatch traces. Core Deliverables: • Fixed source code or PR restoring accurate responses • Technical summary explaining root cause and fixes • Proof of successful test conversations and stable free-flow chat Technical Approach: • Deep dive into your intent-handling logic • Inspect session state management in Redis • Validate Rasa NLU training data and dialogue flow • Verify integration between components in Docker environment I also provide post-delivery support for maintenance, scaling, and future enhancements. Kind regards, Aaron R.

@omard211

With over 5 years of experience in AI, Full Stack Engineering, and ML, I am well-equipped to delve into the intricacies of your AI chatbot and identify and rectify the issues causing incorrect responses. My proficiency in Python, FastAPI, Docker, AWS, and more aligns perfectly with your tech stack. I've been involved in building similar LLM powered applications and working with root causes is my forte. In my previous project, when faced with a similar problem, I used an investigative approach involving progressively eliminating possible causes by testing out one possible fix at a time. This systematic breakdown allowed me to isolate the problematic area quickly. In one case, I identified an erroneous classifying model as the root cause.

@waleeds05

Hi! I see your AI chatbot’s not responding right, which can be super frustrating. I can definitely help you get that fixed. Here’s the plan: I’ll dive into the intent-handling flow, isolate the issue, and come up with a clean patch or PR that'll get your bot back on track. I’ve worked on similar issues before, focusing on Python and Rasa, so I know how to tackle the quirks in those frameworks. I can have the initial fix ready for you in about 3 days. Just need access to your codebase and those logs you mentioned. Once I've patched it up, I’ll send over a quick summary of what went wrong and proof that everything's working as it should. Does that sound good? Best regards, Walled Saleem

@haseebs74

Hi, This looks like a state dialogue flow issue, not the model itself. In setups like FastAPI + Rasa + Redis, empty or wrong replies usually come from session state not restoring properly, fallback triggers firing too early, or timeout/async issues between services. I’ll trace the full flow from intent → Rasa → Redis → response, find exactly where it breaks, and fix it without affecting other parts of the system. You’ll get: Clean fix / PR Short note on root cause Proof with your test chats + 30 min stable run Once you share access, I can start right away.

@webom01

As a skilled Full Stack Developer, I understand the importance of maintaining a well-functioning chatbot. Although I primarily specialize in the MERN stack for web development, my proficiency extends to Python and Java, which are essential for this project. I have experience in building data-driven applications, APIs, and systems that require deep problem-solving skills and attention to detail – qualities that will be crucial for fixing your AI chatbot. In my previous projects, I have regularly demonstrated my ability to identify and resolve complex bugs, even in codebases that weren't originally mine. I'm proficient in utilizing tools like CloudWatch and logs for effective debugging. Once I gain access to your private repository, I'll thoroughly examine the intent-handling flow and identify the root cause behind empty or incorrect responses from your chatbot. I pride myself on delivering clean, efficient code that solves the problem at hand – by contracting me, you're ensuring a reliable patch or pull-request to restore consistent and context-aware answers for your chatbot.

@MuhammadAkif8

Hi, As an experienced full stack developer, I believe I am the right person to solve the issues plaguing your AI chatbot. My proficiency in Python 3.9, FastAPI, Rasa NLU/ dialogue, Redis, Docker, and AWS ECS aligns seamlessly with your tech stack which ensures a smooth debugging process for me. I have an impressive track record in identifying and fixing bugs efficiently and effectively. I understand that every issue has its own unique complexities, but my approach remains consistent - thorough code analysis, root cause identification, and deliverance of clean solutions. Upon completion, I will also provide a detailed technical summary of the bug fix that will not only ensure your AI chatbot functions flawlessly but also enhance your knowledge of its improved intent-handling flow. Warm regards Akif A

@Samadkiyani

I’m your ideal candidate for several key reasons. Firstly, my in-depth knowledge and extensive experience in Python 3.9, FastAPI, Rasa NLU/dialogue, Redis and Docker on AWS ECS provide a solid foundation for understanding your tech stack intimately. Over the years, I've had practical firsthand encounters resolving complexities similar to what you've described with chatbots. This makes me proficient in quickly isolating bugs within codebases, successfully solving them, and delivering consistent and context-aware results which align with your project requirement. Secondly, my ability to adapt and dive deep into any project enables me to perceive the bigger picture while zooming in on the finer details. This uniquely qualifies me to offer nuanced insights during our collaboration which can greatly benefit your chatbot's performance. Lastly, time is money for both of us. I take pride in understanding the urgency of projects and will hit the ground running as soon as access is granted. Specifically, I'd fix the faulty responses of your chatbot by identifying the root cause and provide a clean patch or pull-request that reinstates accurate answers ASAP. Choose me today and let's build a holistic solution that delivers consistent outputs for your AI chatbot.

@christiaanstimie

I already see a clean way to execute this. I specialize in debugging and improving AI chatbots, especially around intent handling, context tracking, and response generation. I’ve fixed bots that were giving empty, irrelevant, or repetitive answers, and I’m confident I can quickly trace why your bot is misfiring and get it back to reliable, useful replies. You want a chatbot that consistently understands what users mean and responds with accurate, complete answers instead of blanks or nonsense. In simple terms: less frustration, more helpful conversations, and a bot you can trust to handle real users. My focus would be on reviewing your current intent-handling logic, checking how messages flow through your NLU/NLP layer, and tightening the mapping between user inputs and responses so it performs well in real-world usage. Before I suggest specifics, is your chatbot built on Dialogflow, Rasa, custom code, or another platform? Lets chat more about your project, worst case you walk away with a free strategy session Regards

@hakan1022

Hi, there! I recently resolved issues in an AI chatbot built with Python and FastAPI, where the bot was providing incorrect or empty responses. In that project, I identified flaws in the intent-handling flow and made adjustments to improve the accuracy and context-awareness of the bot's replies. To tackle the issue, I thoroughly examined the conversation logs and traced the execution flow using debugging tools. A significant challenge was ensuring that the context was maintained throughout the conversation, which I addressed by refining the session management with Redis and enhancing the dialogue management logic in Rasa NLU. For your chatbot, I offer to dive into the codebase, isolate the bugs causing the incorrect responses, and deliver a clean patch or pull request that restores consistent functionality. My approach will include providing a technical summary of the root causes and the changes made, along with proof that the bot responds correctly to the supplied test conversations. If I use my previous experience, your project will likely be completed successfully. Hope to discuss this in detail. Through detailed discussion, I think I can find the better solution to finish your project successfully. Thank you.

@DiaaM123

I will resolve your chatbot’s intent-handling issues by performing a systematic audit of the FastAPI-to-Rasa communication bridge and the Redis session state consistency. Given your stack, "empty or wrong" responses often stem from asynchronous race conditions in FastAPI or a mismatch in how the Rasa TrackerStore retrieves session data from Redis.

@anverd2

My skills align perfectly with your project requirements. I understand you need a clean, professional fix that ensures your AI chatbot delivers seamless, context-aware, and automated responses within your Python 3.9, FastAPI, and Rasa stack, supported by Redis and Docker on AWS ECS. I offer thorough code debugging, pinpointing root causes, and delivering user-friendly, integrated solutions. Even though I’m new here, I have plenty of hands-on experience and have successfully handled projects beyond this platform. I would love to chat more about your project! You’re welcome to contact me for a no-cost consultation anytime. Regards, Anver